The very nature of decentralisation hinges on the ability of the lowest levels of government to quantify and manage their needs and capabilities. Governments need timely and reliable facts to ensure correct resource allocation and design relevant policies. In the absence of efficient and effective data management systems in India (Some pieces may be accessed here, here, here, here and here. ), it is no surprise that countless government schemes in India fail to achieve their stated objectives. Given the need to converge massive bits of information into comparable, numeric formats – the importance of data management in government cannot be overemphasised.

A recent Government of India document looking to evaluate the annual work plan of Chhattisgarh government’s MDM scheme notes that there are wide discrepancies in scheme related numbers captured by the state’s MIS system and those reported by the state government in their annual work plan. [1] It notes that in spite of the fact that nearly 100% of data required under the MDM-MIS Portal has been entered and compiled, there were wide variations between the two sources of information, particularly in the coverage of children, engagement of cook cum helpers, payment of honorarium to cook-cum-helpers, utilisation of cooking cost, utilisation of foodgrains, availability of kitchen-cum-stores, availability of drinking water and toilet facilities.

The SSA website proclaims that “A computerized annual educational MIS system (DISE) is operational in the country.” [2] In theory, the very idea behind putting in place a sophisticated EMIS system is that school level data can be collected, computerised and collated upwards to the block, district and eventually the state level – ensuring that state level plans are an aggregation of school level needs. In reality this is rarely so and the Chhattisgarh case is hardly an exception.

To be clear – it is mandatory that data be entered at all levels, be compiled and sent upwards in a timely manner in pre-determined formats. Both time and money are intensively engaged at all levels of government to ensure that this is indeed so – be it in the form of data entry operators, creation, circulation and updating of formats for data entry, setting up sophisticated computing systems, training of people and basically leaving no stone unturned in making sure we get the most diligently filled excel sheets where the numbers all add up. But to what end is this data that is so industriously churned out? It is seldom used or even relevant for government planning which is often carried out as a separate exercise on its own. At best it finds its way in to published reports where it is referred to for academic papers published with disclaimers about its use and authenticity.

It may be interesting to explore the reasons behind why inconsistency and often utter uselessness of government data is such a fundamental feature running across government programmes and schemes. The answers lie – as do many others to far more complex, existential questions – within the depths of the very nature of government functioning.

Most importantly, the capture, analysis, sharing, storage, transfer and visualization of government programme data are all viewed as exercises in isolation. Setting up the government database is seen as an end in itself with nearly no emphasis on its use and integration into the larger planning process – the reason why it is ostensibly put in place to begin with. The eventual planning exercise carried out at the state or even district level makes little or no reference to numbers collated from the school level upwards. Where a state government would plan to open another elementary school or appoint another teacher is not so much a function of the relative needs of the region, but that of the government’s political compulsions and the ability of the teacher to access the powerful teacher lobby. In such a scenario is it surprising that schools and districts rarely take the planning process seriously?

As the deadline for data submission approaches, school, block and district officers will often shut themselves in a room with a bunch of last year’s excel sheets, updating them based on their “experience and understanding” and hopefully informed guess-estimates. Given the size of the budget available for this exercise, the process may be fuelled by an endless stream of chai and snacks, perhaps even carried out over a period of few days on a retreat, in hotel rooms of state capitals where all officers would gather. The casual nature of the approach can be seen to directly come from the fact that those engaged in filling the numbers in are fully aware that no use will be made of these numbers going forward. This sets in place therefore a vicious circle of irrelevant data and no one using it to make any plans.

A 2013 report by the Planning Commission’s think tank IAMR (Institute of Applied Manpower Research) found that government data across most schemes was either incomplete or inconsistent. It observes that an effective MIS should take governance away from an overemphasis on “rule based approaches that primarily focused on process regulation, in compliance with centrally prescribed standards and rules”. However, the way the MIS is designed and executed in India it does precisely this. Even when an officer is evaluated for his work  for filling up the data sheets, what is assessed is whether a completed form or data sheet was sent in time and not whether this data was of any use or even accurate to begin with. There are no cross checks and no analysis of data coming in over a period of time to evaluate performance. To put it simply in the planning jargon – while the ‘output’ has been taken care of, the eventual ‘outcome’ is ignored.  While it is true that MIS alone cannot be expected to evaluate outcomes, its execution and design must ensure the effective monitoring of “the relationship between inputs, processes and outputs.”[3]

This isn’t merely the case with education or other scheme-related data. Large and often embarrassing inconsistencies have often been found in government macroeconomic data too such as GDP growth rates, WPI and IIP numbers. India’s exports for April- October 2011 had to be revised down by nearly 9 billion USD owing to “double counting”. While there exist simpler and direct explanations for all these inconsistencies (double counting, changes in categorisation from one year to another etc.), the fundamental nature of the government data collection and use process underlying all of these remain the same and reflect the problem outlined above. As this article notes, “in government, the right hand often does not know what the left hand is up to”. Everyone does their task and moves on with little or no integration into the larger picture.

 

 

 

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[1]                      http://mdm.nic.in/Files/PAB/PAB2014-15/Chhattisgarh/8_Chhattisgarh_PAB-2014-15_Minutes.pdf

[2]                      http://ssa.nic.in/ssa-framework/quality-issues-in-elementary-education

[3]Management Information System (MIS) of Indian Government’s Flagship Programmes: Are they an adequate monitoring tool? (IAMR Occasional Paper No. 5/2012)